Matthew J. Ferrari
- Modeling and Simulation top 0.1%
- COVID-19 epidemiological studies 57
- Health top 0.5%
- Vaccine Coverage and Hesitancy 32
- Infectious Diseases top 2%
- Viral Infections and Outbreaks Research 10
- Epidemiology top 2%
- Virology and Viral Diseases 36
- Influenza Virus Research Studies 17
- Agronomy and Crop Science top 2%
- Animal Disease Management and Epidemiology 15
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- Immune responses and vaccinations 11
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- Plant Virus Research Studies 10
- Co-authors
- Bryan T. GrenfellOttar N. BjørnstadNita BhartiAndrew J. TatemC. Jessica E. MetcalfRebecca F. GraisKatriona SheaAli Djibo
- Journals
- Nature (1 paper)Science (5 papers)Proceedings of the National Academy of Sciences (4 papers)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Matthew J. Ferrari
107 papers receiving 3.4k citations
Peers
Comparison fields: 5 of 158
- Modeling and Simulation 1.3k
- Health 880
- Infectious Diseases 828
- Epidemiology 1.4k
- Agronomy and Crop Science 313
Countries citing papers authored by Matthew J. Ferrari
This map shows the geographic impact of Matthew J. Ferrari's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthew J. Ferrari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew J. Ferrari more than expected).
Fields of papers citing papers by Matthew J. Ferrari
This network shows the impact of papers produced by Matthew J. Ferrari. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthew J. Ferrari. The network helps show where Matthew J. Ferrari may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Matthew J. Ferrari, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 4 | |
| 2 | 2022 | 9 | |
| 3 | 2022 | 5 | |
| 4 | 2021 | 2 | |
| 5 | 2021 | 8 | |
| 6 | 2021 | 11 | |
| 7 | 2021 | 7 | |
| 8 | 2020 | 88 | |
| 9 | 2020 | 2 | |
| 10 | 2019 | 12 | |
| 11 | 2018 | 8 | |
| 12 | 2018 | 51 | |
| 13 | 2017 | 34 | |
| 14 | 2017 | 13 | |
| 15 | 2017 | 34 | |
| 16 | 2014 | 2 | |
| 17 | 2014 | 18 | |
| 18 | 2010 | 24 | |
| 19 | 2009 | 23 | |
| 20 | 2008 | 2 |
About Matthew J. Ferrari
Matthew J. Ferrari is a scholar working on Modeling and Simulation, Health and Agronomy and Crop Science, having authored 112 papers that have together received 3.6k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (57 papers), Virology and Viral Diseases (36 papers), Vaccine Coverage and Hesitancy (32 papers), Influenza Virus Research Studies (17 papers), Animal Disease Management and Epidemiology (15 papers), Immune responses and vaccinations (11 papers), Plant Virus Research Studies (10 papers) and Viral Infections and Outbreaks Research (10 papers). The work is most often cited by research in Modeling and Simulation (1.3k citations), Health (880 citations) and Infectious Diseases (828 citations). Matthew J. Ferrari has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Bryan T. Grenfell, Ottar N. Bjørnstad, Nita Bharti, Andrew J. Tatem, C. Jessica E. Metcalf, Rebecca F. Grais, Katriona Shea, Ali Djibo, Justin Lessler and Saki Takahashi. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.